Open-set semantic segmentation remains yet a challenging task, not only due to the
inherent challenges of pixel-wise classification but also the precise segmentation of …

Abstract Grounded Situation Recognition (GSR) is capable of recognizing and interpreting
visual scenes in a contextually intuitive way, yielding salient activities (verbs) and the …

Semantic segmentation has received wide attention as a feasible solution to effectively
interpret the information in remote sensing images. Solutions are typically built with a static …

In real-world classification tasks, deep neural networks show innovative performance in
various fields. However, traditional classification methods are constructed based on a set of …

Tattoos can serve as an essential source of biometric information for public security, aiding
in identifying suspects and victims. In order to automate tattoo classification, tasks like …

Collecting samples that exhaust all possible classes for real-world tasks is usually hard or
even impossible due to many different factors. In a realistic/feasible scenario, methods …

Open-set segmentation has caught the community's attention only in the last few years, and
it is a growing and active research area with many challenges ahead. To better identify open …

This study presents a novel AI method for extracting polygon and point features from
historical geologic maps, representing a pivotal step for assessing the mineral resources …

Segmenting and classifying satellite and aerial images is a crucial task for understanding
various environmental, urban, and agricultural phenomena in remote sensing. Traditional …

Neves de Oliveira, Hugo. Segmentação semântica de conjunto aberto aplicada a imagens de
sensoriamento remoto. Rio de Janeiro, 2023. 211p. Tese de Doutorado–Departamento de …